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Adaptive variable location kernel density estimators with good performance at boundaries

Park, B. U.; Jeong, Seok-Oh; Jones, M. C. and Kang, Kee-Hoon (2003). Adaptive variable location kernel density estimators with good performance at boundaries. Journal of Nonparametric Statistics, 15(1) pp. 61–75.

DOI (Digital Object Identifier) Link: http://dx.doi.org/10.1080/10485250306041
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Abstract

This paper introduces new adaptive versions of the variable location density estimator which, for the first time, achieve bias improvement by an order of magnitude at the boundaries, as well as affording the usual higher order bias in the interior of the density support. We develop a general theoretical framework into which both these and earlier versions of adaptive variable location density estimators fit. This enables us to provide a single formula for the higher order biases and variances of these estimators. Numerical work for the comparison of these estimators with each other and with the conventional kernel density estimator reveals good properties of the proposed estimators.

Item Type: Journal Article
Copyright Holders: 2003 Taylor & Francis Ltd.
ISSN: 1048-5252
Keywords: kernel density estimation; bias reduction; estimation at boundaries; variable location; data sharpening
Academic Unit/Department: Mathematics, Computing and Technology > Mathematics and Statistics
Item ID: 22639
Depositing User: Sarah Frain
Date Deposited: 12 Aug 2010 12:00
Last Modified: 02 Dec 2010 21:02
URI: http://oro.open.ac.uk/id/eprint/22639
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